JP6464345B2 - Weight distribution acquisition device, weight distribution acquisition method and program - Google Patents

Description

  The present invention relates to a weight distribution acquisition device, a weight distribution acquisition method, and a program.

In Patent Document 1, an instantaneous rotational force is given to a timber, the acceleration or angular acceleration at that time is measured, and the water distribution in the timber is determined based on the relative difference in the measured values for each timber. A moisture measurement method is described.
In Patent Document 1, this allows non-destructive, simple, and reliable detection of the moisture state of wood with a relatively large cross section, such as residential beams, girders, and pillars, to the gradient of internal and external moisture. It is possible to grasp the density.

JP 2009-270874 A

  As described above, Patent Document 1 describes that the moisture content between the inside and outside of wood is grasped. On the other hand, it is desired that the mass distribution of the object can be obtained in more detail without being limited to the wood and not only the inside and the outside.

  The present invention provides an apparatus, a method, and a program capable of obtaining a mass distribution when an arbitrary object capable of measuring a moment of inertia is divided into arbitrary portions.

  According to the first aspect of the present invention, the mass distribution acquisition device includes an inertia moment acquisition unit that acquires a measurement value of the inertia moment of the object for each of the plurality of rotation axes, and the inertia acquired by the inertia moment acquisition unit. A mass distribution obtaining unit for obtaining a mass distribution of the object based on the moment.

  You may make it provide the shape determination part which determines the shape of the said target object based on the mass distribution which the said mass distribution acquisition part acquired.

  According to the second aspect of the present invention, the mass distribution acquisition method is obtained by the inertia moment acquisition step of acquiring the measurement value of the inertia moment of the object for each of the plurality of rotation axes, and the inertia moment acquisition step. A mass distribution obtaining step for obtaining a mass distribution of the object based on the inertia moment.

  According to the third aspect of the present invention, the program is obtained by the inertia moment acquisition step of acquiring the measurement value of the inertia moment of the object for each of the plurality of rotation axes, and the inertia moment acquisition step. A mass distribution obtaining step for obtaining a mass distribution of the object based on the inertia moment.

  According to the present invention, it is possible to provide an apparatus, a method, and a program capable of obtaining a mass distribution when an arbitrary object whose moment of inertia can be measured is divided into arbitrary portions.

It is a schematic block diagram which shows the function structure of the mass distribution acquisition system in one Embodiment of this invention. It is a schematic external view which shows the example of the external shape of the inertia moment measuring apparatus in the embodiment. It is a figure which shows the example of the elongate stick | rod which has two parts from which the density differs in the same embodiment. It is a figure which shows the example of the elongate stick | rod which has n part from which the density differs in the same embodiment. It is a figure which shows the example of the target object which has the part of two cylinders from which the density differs in the same embodiment. It is a figure which shows the example of the target object which has the part of n cylinders from which the density differs in the same embodiment. It is a figure which shows the example of the estimation result of mass distribution in the same embodiment. It is the figure which expanded the vicinity of a correct value and an estimated value among the mass distribution estimation results of FIG. It is a figure which shows the example of the estimation result of mass distribution in the same embodiment. It is the figure which expanded the vicinity of a correct value and an estimated value among the mass distribution estimation results of FIG. It is a flowchart which shows the example of the process sequence which a mass distribution acquisition apparatus performs in this embodiment.

Hereinafter, although embodiment of this invention is described, the following embodiment does not limit the invention concerning a claim. In addition, not all the combinations of features described in the embodiments are essential for the solving means of the invention.
In the description of the specification, bold notation indicating vectors or matrices is omitted.

<First Embodiment>
FIG. 1 is a schematic block diagram illustrating a functional configuration of a mass distribution acquisition system according to an embodiment of the present invention. In FIG. 1, the mass distribution acquisition system 1 includes an inertia moment measurement device 10 and a mass distribution acquisition device 20. The inertia moment measuring device 10 includes a rotation drive unit 11, an angular velocity detection unit 12, and an inertia moment calculation unit 13. The mass distribution acquisition device 20 includes an inertia moment acquisition unit 21, a mass distribution acquisition unit 22, a shape determination unit 23, and a result output unit 24.

The inertia moment measuring apparatus 10 measures the inertia moment of an object whose mass distribution is to be obtained.
The rotation drive unit 11 includes power such as a motor, and rotates an object placed on the inertia moment measurement device 10.
The angular velocity detection unit 12 detects an angular velocity when the rotation driving unit 11 rotates the object.
The inertia moment calculator 13 calculates the inertia moment of the object based on the angular velocity detected by the angular velocity detector 12. Specifically, when the rotation drive unit 11 outputs the rotation energy K and the angular velocity detection unit 12 detects the angular velocity ω, the inertia moment calculation unit 13 calculates the inertia moment I = 2K / ω ² .

FIG. 2 is a schematic external view showing an example of the external shape of the moment of inertia measuring apparatus 10. In FIG. 1, the inertia moment measuring apparatus 10 includes a main body 101, a rotating shaft 102, and a rotating table 103.
The main body 101 accommodates the rotation drive unit 11, and the rotation drive unit 11 applies a rotation force to the rotation shaft 102, so that the rotation shaft 102, the rotation table 103, and the target placed on the rotation table 103. The object b100 is rotated. The main body 101 houses an angular velocity detection unit 12 and detects an angular velocity at which the rotating shaft 102 rotates (= an angular velocity at which the object b100 rotates). The inertia moment calculation unit 13 may also be housed in the main body 101 or may be provided as a separate device from the inertia moment measurement device 10. For example, the inertia moment calculation unit 13 may be realized using a general-purpose computer provided separately from the inertia moment measurement device 10.

The rotating shaft 102 transmits the rotational force from the rotation driving unit 11 to the turntable 103.
The turntable 103 receives a load of objects. And the turntable 103 rotates the target object b100 by rotating with the rotational force transmitted from the rotating shaft 102 in the state in which the target object was mounted.
Note that the inertia moment of the inertia moment measuring device 10 such as the inertia moment of the turntable 103 and the inertia moment of the fixing jig that fixes the object b100 may be obtained in advance. Then, the inertia moment calculation unit 13 stores these inertia moments in advance, and performs correction to reduce the influence of the inertia moment of the inertia moment measuring device 10 when calculating the inertia moment of the object b100. May be. Thereby, the moment of inertia of the object b100 can be obtained with higher accuracy.
Alternatively, an energy loss due to friction or the like may be estimated in advance by mounting an object having a known moment of inertia on the turntable 103 and measuring the angular velocity. Then, when the inertia moment calculation unit 13 calculates the inertia moment of the object b, the inertia moment calculation unit 13 may perform correction to reduce the influence of the energy loss. Thereby, the moment of inertia of the object b100 can be obtained with higher accuracy.

The mass distribution acquisition device 20 obtains a mass distribution in the object based on the moment of inertia measured by the moment of inertia measurement device 10. In particular, the inertia moment measuring device 10 measures the inertia moment of the object for each of a plurality of rotation centers, and the mass distribution acquisition device 20 obtains the mass distribution of the object based on the plurality of inertia moments. The mass distribution acquisition device 20 is realized using, for example, a computer.
The inertia moment acquisition unit 21 acquires a measured value of the inertia moment of the object measured by the inertia moment measurement device.

The mass distribution acquisition unit 22 acquires (calculates) the mass distribution of the object based on the inertia moment acquired by the inertia moment acquisition unit.
The shape determination unit 23 determines the shape of the object based on the mass distribution acquired by the mass distribution acquisition unit 22. Specifically, the shape determination unit 23 is a part in which the mass is equal to or less than a predetermined threshold for each part in which the target region (the space including the target object that is processed by the mass distribution acquisition device 20) is divided. It is determined that the object does not exist.

The result output unit 24 outputs information indicating the mass distribution acquired by the mass distribution acquisition unit 22. The result output unit 24 outputs information indicating the shape of the object acquired by the shape determination unit 23. Various methods can be used as a method in which the result output unit outputs information indicating the mass distribution and a method of outputting information indicating the shape. For example, the result output unit 24 may have a display screen such as a liquid crystal panel and display such information. Alternatively, the result output unit 24 may include a communication circuit and transmit these pieces of information to other devices.
In the mass distribution acquisition device 20, the shape determination unit 23 is not essential. The mass distribution acquisition device 20 may not include the shape determination unit 23.

Next, processing in which the mass distribution acquisition unit 22 obtains the mass distribution of the object from the moment of inertia will be described.
First, it will be described that if the size of the object is determined, the relationship between the mass distribution of the object and the moment of inertia at an arbitrary rotation center can be obtained.
A rigid body rotating at an angular velocity ω with a certain straight line as the rotation center (rotation axis) is divided into n small parts. At this time, the kinetic energy K _i possessed by the small portion of the rotation radius r _i and the mass m _i is expressed as in Expression (1).

  Therefore, the kinetic energy of the entire object is expressed as shown in Equation (2).

  However, I shows a moment of inertia and is expressed as in equation (3).

Therefore, the moment of inertia I can be obtained by adding kinetic energy (rotational energy) to the object and measuring the angular velocity ω at that time.
Note that if the mass of the minute volume ΔV is Δm, the density ρ is expressed as shown in Equation (4).

  By bringing the volume of the minute portion close to 0, the moment of inertia I is expressed by an integral equation such as equation (5).

Next, the estimation of the mass distribution will be described by taking an elongate bar having two parts having different densities as an example.
FIG. 3 is a diagram showing an example of an elongated bar having two parts having different densities. The bar b111 (target object) shown in the figure is configured by combining a part b121 and a part b122 in the order of b121 and b122 from the left in the figure. The length of the portion b121 is l ₁ , the cross-sectional area is S ₁ , and the mass is w ₁ . The length of the portion b122 is l ₂ , the cross-sectional area is S ₂ , and the mass is w ₂ .
The density of the part b121 and the density of the part b122 are ρ ₁ and ρ ₂ , respectively, and the distance of the rotation axis from the left end of the part b121 is t (0 ≦ t ≦ l1). With respect to the distance z from the rotation axis, the moment of inertia I (t) is expressed as in Equation (6).

Here, the distances from the left end of the portion b121 of two different rotation axes are t ₁ and t ₂ respectively, and the moment of inertia when the rod b111 is rotated by each of these two rotation axes is I (t ₁ ). , I (t ₂ ). If these moments of inertia I (t ₁ ) and I (t ₂ ) can be measured with high accuracy, the mass of each part can be obtained from the quadratic simultaneous equations shown in equation (7).

  When Expression (7) is expressed as a determinant, Expression (8) is obtained.

Here, I ₂ , R ₂₂ , and W ₂ are determined as in Expression (9).

I ₂ , R ₂₂ , and W ₂ are an inertia moment vector, a response matrix, and a mass vector, respectively.
Expression (8) is expressed as Expression (10).

Assuming that the inverse matrix of the response matrix R ₂₂ is R ₂₂ ⁻ , the equation for obtaining the mass vector W ₂ is as shown in Equation (11).

In this way, a response matrix R ₂₂ indicating the relationship between the moment of inertia vector I ₂ and the mass vector W ₂ can be obtained in advance. The mass vector W ₂ can be estimated by obtaining the moment of inertia vector I ₂ by measurement.
Furthermore, the position of the rotation axis (distance from the left edge portion b121) increasing the number of measurements of the moment of inertia by changing the m different from _{t 1} to _{t m,} measured from the I _{(t 1)} to I _{(t m)} When estimating mass using data, Formula (8) becomes like Formula (12).

  Moreover, Formula (10) becomes like Formula (13).

However, I _m and R _m2 are expressed as in Expression (14).

On the other hand, W ₂ is the same as that shown in Expression (9).
Actually, since the measurement error E _rr is added to the moment of inertia vector I _m , the equation (15) is obtained.

The inertia moment vector I _m-m indicates _m inertia moments measured by changing the position of the rotation axis in m ways.
By using more measurement data than unknowns, the reliability of the solution can be increased by the least square method or the like.

Next, the estimation of the mass distribution will be described by taking an elongate bar having n portions with different densities as an example.
FIG. 4 is a diagram showing an example of an elongated bar having n parts having different densities. The bar b211 shown in the figure is configured such that a part b221, a part b222,..., A part b22n are joined in the order of b221, b222,. Yes. The length of the part b221 is l ₁ , the cross-sectional area is S ₁ , and the mass is w ₁ . The length of the part b222 is l ₂ , the cross-sectional area is S ₂ , and the mass is w ₂ . Length of ... part b22n is _{l n,} the cross-sectional area is _{S n,} the mass _{w n.}
In this case, Expression (15) becomes Expression (16).

Here, R _mn is a response matrix obtained by extending R _m2 to n columns. W _n is a vector obtained by extending W ₂ to n dimensions. The content of R _mn (value of each element) can be determined based on the position of the rotation axis and the size of the region of interest. The attention area here is a space for which mass is obtained.
Based on Expression (16), Expression (17) for obtaining an estimated vector W _n ′ of the mass distribution can be obtained.

Here, R _mn ⁺ represents a Moore-Penrose general inverse matrix of R _mn . According to the Moore-Penrose general inverse matrix, some inverse matrix can be obtained for an arbitrary response matrix R _mn .
By measuring m moments of inertia with respect to m rotational axes larger than n considering the shape (obtaining m observation equations), it is possible to improve the estimation accuracy of the mass distribution by the least square method or the like.

Expression (17) can be generalized to an arbitrary shape as well as a rod shape. The mass distribution acquisition part 22 calculates | requires mass distribution of a target object based on Formula (17).
Specifically, first, a target area that is a space including the target object is divided into a plurality of parts. For example, the target region is divided into meshes as analysis units. The user of the mass distribution acquisition device 20 may perform the division, or the mass distribution acquisition unit 22 may automatically perform the division.

The mass distribution acquisition unit 22 acquires the Moore-Penrose general inverse matrix R _mn ⁺ of the response matrix. The user of the mass distribution acquisition device 20 may input R _mn ⁺ , or the mass distribution acquisition unit 22 may calculate R _mn ⁺ .
Then, the mass distribution acquisition unit 22 calculates the mass distribution of the object by substituting the measured value of the moment of inertia by the moment of inertia measuring apparatus 10 into the equation (17).

  The mass distribution acquisition unit 22 may acquire a least square general inverse matrix or a norm minimum general inverse matrix instead of the Moore-Penrose general inverse matrix of the response matrix. In particular, when the number of measurements (number of moments of inertia obtained by measurement) is larger than the number of unknowns (number of variables to be solved by the equation), it is conceivable to use a least square general inverse matrix. On the other hand, when the number of measurements is smaller than the unknown, a norm minimum general inverse matrix can be used. The Moore-Penrose general inverse matrix can be applied to cases where the number of measurements is large or small relative to the unknown.

Next, the estimation of mass distribution will be described using an object having two cylindrical portions having different densities as an example.
FIG. 5 is a diagram illustrating an example of an object having two cylindrical portions having different densities. An object b311 shown in the figure is configured by combining two cylindrical parts b321 and b322 in the order of b321 and b322 from the left toward the figure. The length of the portion b321 is l ₁ , the radius is r ₁ , the center of gravity is G ₁ , and the mass is w ₁ . The length of the portion b322 is l ₂ , the radius is r ₂ , the center of gravity is G ₂ , and the mass is w ₂ .
In addition, the distance from the left end of the part b321 to the rotation axis is t, and the distances from the rotation axis to the centers of gravity G ₁ and G ₂ are e ₁ and e ₂ , respectively.
At this time, the moment of inertia _{I G1} around the center of gravity _{G 1} part b321 is expressed by the equation (18).

Further, the moment of inertia _{I G2} around the center of gravity _{G 2} parts b322, is expressed by the equation (19).

The whole object b311, the moment of inertia _{I P} about the point P (around the rotation axis), than parallel axis theorem, the following equation (20).

Here, the distance e ₁ is expressed as in Expression (21).

The distance e ₂ is expressed as in Expression (22).

Therefore, I _p is as shown in Expression (23).

Therefore, even when the masses w ₁ and w ₂ are unknown, the moments of inertia I (t ₁ ) and I (t ₂ ) with respect to the positions of two different rotation axes (positions from the left end of the portion b321) t ₁ and t ₂ respectively. Is obtained with high accuracy, the masses w ₁ and w ₂ can be obtained from the simultaneous equations of the equation (24).

  Here, when Expression (24) is expressed by a determinant, Expression (25) is obtained.

  Expression (25) is expressed as Expression (26).

However, I _{c2 and} R _c22 are expressed as in Expression (27).

_When the inverse matrix of R _c22 is R _c22 ⁻ , equation (27) becomes equation (28).

As shown in Expression (28), if the moments of inertia I _p (t ₁ ) and I _p (t ₂ ) with respect to two different rotation axes (rotation centers) can be obtained, two masses w ₁ and w ₂ are calculated. be able to.
Furthermore, the position t of the rotary shaft to increase the number of measurements of the moment of inertia by changing the m _different, by using the measurement data from the I p _{(t 1)} to _I p _{(t m),} so that equation (29) .

  Expression (29) is expressed as Expression (30).

However, I _{cm and} R _cm2 are expressed as in Expression (31).

Even if the measurement error _{Err of the} moment of inertia is added, the reliability of the solution can be improved by the least square method or the like.
Next, the estimation of mass distribution will be described using an example of an object having n cylindrical portions having different densities.
FIG. 6 is a diagram illustrating an example of an object having n cylindrical portions having different densities. The object b411 shown in the figure has a cylindrical part n421 b421, a part b422,..., A part b42n in the order of b421, b422,. It is composed by connecting with. The length of the portion b421 is l ₁ , the radius is r ₁ , the center of gravity is G ₁ , and the mass is w ₁ . The length of the portion b422 is l ₂ , the radius is r ₂ , the center of gravity is G ₂ , and the mass is w ₂ . Length of ... part b42n is _{l n,} the radius _{r n,} the center of gravity _{G n,} the mass is _{w n.}
The distance from the left end portion b421 to the rotational axis is t, the distance from the axis of rotation to the center of gravity _{G 1, G 2 ··· G n} , _{respectively,} e _1, e 2, · · ·, and _{e n} To do.
In this case, Expression (20) is expanded as Expression (32).

Thereby, the relationship R _cmm between the inertia moment vector I _cm-m including the measured values of _m inertia moments and the mass vector W _n including n unknowns can be calculated. For this reason, the reliability of a solution can be improved by the least squares method etc. like Formula (33) by using m measurement data larger than n.

Based on Expression (33), Expression (34) for obtaining an estimated vector W _n ′ of the mass distribution can be obtained.

Here, R _cmm ⁺ _represents a Moore-Penrose general inverse matrix of R _cmm .
Next, an example of estimating the mass distribution of an elongated bar having two portions having different densities will be described.
Consider the problem of obtaining the mass w ₁ = 360 kilograms (kg) and the mass w ₂ = 240 kilograms for the elongate bar b111 having two parts b121 and b122 of different densities shown in FIG. It is assumed that the lengths of the portions b121 and b122 are l ₁ = 1.2 meters (m) and l ₂ = 3.6 meters, respectively.
The moment of inertia when the rotation axis is at a distance of t (0 ≦ t ≦ l ₁ ) from the left end of the portion b121 is expressed by the above-described equations (12) and (13).
Moreover, Formula (35) is obtained from Formula (13).

Where R _m2 ⁺ represents the Moore-Penrose general inverse matrix of R _m2 .
If the dimensions of the parts b121 and b122 are known, the moment of inertia with respect to the mass distribution can be examined, so that the response matrix R _m2 can be obtained, and the mass from the moment of inertia vector I _m indicating the measured value of the moment of inertia. Distribution can be obtained (estimated).

Now, the position of the rotation axis (distance from the left end of the part b121) t is t ₁ = 0 meter, t ₂ = 0.3 meter, t ₃ = 0.6 meter, t ₄ = 0.9 meter, t ₅ = 1.2 meters, changing to 5 ways, and measuring the moment of inertia and simulating the mass distributions w ₁ and w ₂ . In order to simulate the measured value of the moment of inertia, an error according to a normal distribution having an average of 0 and a standard deviation of 0.4 kilogram square (kgm ² ) was added as a random number to each correct value of the moment of inertia. The standard deviation value 0.4 was determined with reference to an example of a commercially available engine subjectivity moment measuring apparatus.

FIG. 7 is a diagram illustrating an example of a mass distribution estimation result. The figure shows the result of estimating the mass distribution by changing the random number seed to 50 ways. In the figure, the correct value of the mass distribution is indicated by a square (■) and the estimated value is indicated by a circle (◯). Both correct and estimated values are shown in the vicinity of w ₁ = 360 kilograms and w ₂ = 240 kilograms.
FIG. 8 is an enlarged view of the vicinity of the correct answer value and the estimated value in the mass distribution estimation results of FIG. In the figure, a correct value point P101 is displayed at a position of w ₁ = 360 kg and w ₂ = 240 kg. Also, _{w 1} is 360 kg back and _forth, the position in the vicinity of w 2 = 240 kilograms such a point P102, point indicating the estimated value is more displayed.
As shown in FIGS. 7 and 8, the estimation accuracy of w ₂ is particularly high, and w ₁ can also be estimated with an accuracy of about 1 kilogram.

Next, an example of estimating the shape of the object from the estimation of the mass distribution of the object will be described.
Consider the problem of obtaining the mass w ₁ = 360 kilograms and the mass w ₂ = 0 kilograms for the elongated bar b111 having two portions b121 and b122 of different densities shown in FIG. It is assumed that the lengths of the portions b121 and b122 are l ₁ = 1.2 meters (m) and l ₂ = 3.6 meters, respectively. As a result, the length of the object is 1.2 meters, but the shape of the object is unknown, and the case where the mass distribution is obtained for an area of 4.8 meters in length as the attention area is simulated.

Now, the position of the rotation axis (distance from the left end of the part b121) t is t ₁ = 0 meter, t ₂ = 0.3 meter, t ₃ = 0.6 meter, t ₄ = 0.9 meter, t ₅ = 1.2 meters, changing to 5 ways, and measuring the moment of inertia and simulating the mass distributions w ₁ and w ₂ . In order to simulate the measured value of the moment of inertia, an error according to a normal distribution having an average of 0 and a standard deviation of 0.4 kilogram square (kgm ² ) was added as a random number to each correct value of the moment of inertia.

FIG. 9 is a diagram illustrating an example of a mass distribution estimation result. The figure shows the result of estimating the mass distribution by changing the random number seed to 50 ways. In the figure, the correct value of the mass distribution is indicated by a square (■) and the estimated value is indicated by a circle (◯). Both correct values and estimated values are shown in the vicinity of w ₁ = 360 kilograms and w ₂ = 0 kilograms.
FIG. 10 is an enlarged view of the vicinity of the correct answer value and the estimated value in the mass distribution estimation results of FIG. 9. In the figure, a correct value point P201 is displayed at a position of w ₁ = 360 kilograms and w ₂ = 0 kilograms. In addition, a plurality of points indicating estimated values such as a point P202 are displayed at positions where w ₁ is around 360 kilograms and w ₂ = 0 kilograms.
As shown in FIG. 9 and FIG. 10, the estimated value of the mass w ₂ is almost zero.
As described above, the shape determination unit 23 determines that the region in which the mass is substantially 0 is a region where the object does not exist. Thereby, the shape determination part 23 calculates | requires the shape of a target object. Specifically, the shape determination unit 23 determines whether or not the mass is equal to or less than a predetermined threshold for each portion into which the target region is divided. And the shape determination part 23 determines with the target object not existing in the part determined that mass is below a threshold value. Thereby, even if the area | region which the mass distribution acquisition apparatus 20 makes object is set larger than the object area | region, the shape determination part 23 can detect the shape of a target object. Moreover, the shape determination part 23 can detect the cavity inside a target object.

Next, the operation of the mass distribution acquisition device 20 will be described with reference to FIG.
FIG. 11 is a flowchart illustrating an example of a processing procedure performed by the mass distribution acquisition device 20.
In the process of the figure, the moment of inertia acquisition unit 21 acquires the moment of inertia measured by the moment of inertia measuring apparatus 10 for each of the plurality of rotation axes (step S101).
Next, the mass distribution acquisition unit 22 acquires the mass distribution of the object based on the moment of inertia obtained in step S101 (step S102). Specifically, the mass distribution acquisition unit 22 calculates the mass distribution by substituting the moment of inertia obtained in step S101 into the equation (17).
Next, the shape determination unit 23 determines the shape of the object based on the mass distribution obtained in step S102 (step S103). Specifically, the shape determination unit 23 determines that the target object is not present in a portion where the mass is equal to or less than a predetermined threshold among the portions obtained by dividing the target region.
Then, the result output unit 24 outputs the mass distribution of the object obtained in step S102 and the shape of the object obtained in step S103 (step S104).
Then, the process of FIG. 11 is complete | finished.

As described above, the inertia moment acquisition unit 21 acquires the measurement value of the inertia moment of the object for each of the plurality of rotation axes. Then, the mass distribution acquisition unit obtains the mass distribution of the object based on the inertia moment acquired by the inertia moment acquisition unit.
Thereby, the mass distribution acquisition device 20 can obtain the mass distribution when an arbitrary object whose moment of inertia can be measured is divided into arbitrary portions.

In addition, the shape determination unit 23 determines the shape of the object based on the mass distribution acquired by the mass distribution acquisition unit 22.
Thereby, even if the area | region which the mass distribution acquisition apparatus 20 makes object is set larger than the object area | region, the shape determination part 23 can detect the shape of a target object. Moreover, the shape determination part 23 can detect the cavity inside a target object.

It should be noted that a program for realizing all or part of the calculation and control functions performed by the mass distribution acquisition device 20 is recorded on a computer-readable recording medium, and the program recorded on the recording medium is read into a computer system. The processing of each unit may be performed by executing. Here, the “computer system” includes an OS and hardware such as peripheral devices.
Further, the “computer system” includes a homepage providing environment (or display environment) if a WWW system is used.
The “computer-readable recording medium” refers to a storage device such as a flexible medium, a magneto-optical disk, a portable medium such as a ROM and a CD-ROM, and a hard disk incorporated in a computer system. Furthermore, the “computer-readable recording medium” dynamically holds a program for a short time like a communication line when transmitting a program via a network such as the Internet or a communication line such as a telephone line. In this case, a volatile memory in a computer system serving as a server or a client in that case, and a program that holds a program for a certain period of time are also included. The program may be a program for realizing a part of the functions described above, and may be a program capable of realizing the functions described above in combination with a program already recorded in a computer system.

  The embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to this embodiment, and includes design changes and the like without departing from the gist of the present invention.

DESCRIPTION OF SYMBOLS 1 Mass distribution acquisition system 10 Inertia moment measuring device 11 Rotation drive part 12 Angular velocity detection part 13 Inertia moment calculation part 20 Mass distribution acquisition apparatus 21 Inertia moment acquisition part 22 Mass distribution acquisition part 23 Shape determination part 24 Result output part

Claims (4)

An inertia moment acquisition unit that acquires the moment of inertia by rotating the object around a plurality of points whose positions from the reference point in the object are known ;
Based on the moment of inertia acquired by the moment of inertia acquisition unit and the position of the rotation axis at that time, a mass distribution of the object is obtained using an inertia moment vector, a response matrix, a mass vector, and an inverse matrix of the response matrix. A mass distribution acquisition unit;
A mass distribution acquisition device comprising: Based on the mass distribution acquired by the mass distribution acquisition unit, a shape determination unit that determines the shape of the object,
The mass distribution acquisition apparatus according to claim 1. A moment of inertia acquisition step of acquiring a moment of inertia by rotating the object around a plurality of points whose positions from the reference point in the object are known ;
Based on the moment of inertia obtained in the moment of inertia acquisition step and the position of the rotation axis at that time , the moment of inertia vector, response matrix, mass vector, and mass distribution of the object using the inverse matrix of the response matrix Obtaining a mass distribution,
A mass distribution acquisition method comprising: On the computer,
A moment of inertia acquisition step of acquiring a moment of inertia by rotating the object around a plurality of points whose positions from the reference point in the object are known ;
Based on the moment of inertia obtained in the moment of inertia acquisition step and the position of the rotation axis at that time , the moment of inertia vector, response matrix, mass vector, and mass distribution of the object using the inverse matrix of the response matrix Obtaining a mass distribution,
A program for running

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